Complexity synchronization analysis of neurophysiological data: Theory and methods
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arXiv
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| Autori principali: | , , , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866910708308901888 |
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| author | Schizas, Ioannis Sullivan, Sabrina Kerick, Scott E. Mahmoodi, Korosh Bradford, J. Cortney Boothe, David L. Franaszczuk, Piotr J. Grigolini, Paolo West, Bruce J. |
| author_facet | Schizas, Ioannis Sullivan, Sabrina Kerick, Scott E. Mahmoodi, Korosh Bradford, J. Cortney Boothe, David L. Franaszczuk, Piotr J. Grigolini, Paolo West, Bruce J. |
| contents | We apply modified diffusion entropy analysis (MDEA) to assess multifractal dimensions of ON time series (ONTS) and complexity synchronization (CS) analysis to infer information transfer among ONs that are part of a network of organ networks (NoONs). The purpose of this paper is to advance the validation, standardization, and repeatability of MDEA and CS analysis of heterogeneous neurophysiological time series data. Results from processing these datasets show that the complexity of brain, heart, and lung ONTS significantly co-vary over time during cognitive task performance but that certain principles, guidelines, and strategies for the application of MDEA analysis need consideration. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2411_14602 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Complexity synchronization analysis of neurophysiological data: Theory and methods Schizas, Ioannis Sullivan, Sabrina Kerick, Scott E. Mahmoodi, Korosh Bradford, J. Cortney Boothe, David L. Franaszczuk, Piotr J. Grigolini, Paolo West, Bruce J. Neurons and Cognition Adaptation and Self-Organizing Systems We apply modified diffusion entropy analysis (MDEA) to assess multifractal dimensions of ON time series (ONTS) and complexity synchronization (CS) analysis to infer information transfer among ONs that are part of a network of organ networks (NoONs). The purpose of this paper is to advance the validation, standardization, and repeatability of MDEA and CS analysis of heterogeneous neurophysiological time series data. Results from processing these datasets show that the complexity of brain, heart, and lung ONTS significantly co-vary over time during cognitive task performance but that certain principles, guidelines, and strategies for the application of MDEA analysis need consideration. |
| title | Complexity synchronization analysis of neurophysiological data: Theory and methods |
| topic | Neurons and Cognition Adaptation and Self-Organizing Systems |
| url | https://arxiv.org/abs/2411.14602 |